Prediction of orientation selectivity from receptive field architecture in simple cells of cat visual cortex

Analytic Model for Feature Maps in the Primary Visual Cortex

A compact analytic model is proposed to describe the combined orientation preference (OP) and ocular dominance (OD) features of simple cells and their mutual constraints on the spatial layout of the combined OP-OD map in the primary visual cortex (V1). This model consists of three parts: (i) an anisotropic Laplacian (AL) operator that represents the local neural sensitivity to the orientation of visual inputs; and (ii) obtain a receptive field (RF) operator that models the anisotropic spatial projection from nearby neurons to a given V1 cell over scales of a few tenths of a millimeter and combines with the AL operator to give an overall OP operator; and (iii) a map that describes how the parameters of these operators vary approximately periodically across V1. The parameters of the proposed model maximize the neural response at a given OP with an OP tuning curve fitted to experimental results. It is found that the anisotropy of the AL operator does not significantly affect OP selectivity, which is dominated by the RF anisotropy, consistent with Hubel and Wiesel's original conclusions that orientation tuning width of V1 simple cell is inversely related to the elongation of its RF. A simplified and idealized OP-OD map is then constructed to describe the approximately periodic local OP-OD structure of V1 in a compact form. It is shown explicitly that the OP map can be approximated by retaining its dominant spatial Fourier coefficients, which are shown to suffice to reconstruct its basic spatial structure. Moreover, this representation is a suitable form to analyze observed OP maps compactly and to be used in neural field theory (NFT) for analyzing activity modulated by the OP-OD structure of V1. Application to independently simulated V1 OP structure shows that observed irregularities in the map correspond to a spread of dominant coefficients in a circle in Fourier space. In addition, there is a strong bias toward two perpendicular directions when only a small patch of local map is included. The bias is decreased as the amount of V1 included in the Fourier transform is increased.

Predicting Grating Orientations With Cross-Frequency Coupling and Least Absolute Shrinkage and Selection Operator in V1 and V4 of Rhesus Monkeys

Orientation selectivity, as an emergent property of neurons in the visual cortex, is of critical importance in the processing of visual information. Characterizing the orientation selectivity based on neuronal firing activities or local field potentials (LFPs) is a hot topic of current research. In this paper, we used cross-frequency coupling and least absolute shrinkage and selection operator (LASSO) to predict the grating orientations in V1 and V4 of two rhesus monkeys. The experimental data were recorded by utilizing two chronically implanted multi-electrode arrays, which were placed, respectively, in V1 and V4 of two rhesus monkeys performing a selective visual attention task. The phase-amplitude coupling (PAC) and amplitude-amplitude coupling (AAC) were employed to characterize the cross-frequency coupling of LFPs under sinusoidal grating stimuli with different orientations. Then, a LASSO logistic regression model was constructed to predict the grating orientation based on the strength of PAC and AAC. Moreover, the cross-validation method was used to evaluate the performance of the model. It was found that the average accuracy of the prediction based on the combination of PAC and AAC was 73.9%, which was higher than the predicting accuracy with PAC or AAC separately. In conclusion, a LASSO logistic regression model was introduced in this study, which can predict the grating orientations with relatively high accuracy by using PAC and AAC together. Our results suggest that the principle behind the LASSO model is probably an alternative direction to explore the mechanism for generating orientation selectivity.

Long-range connections enrich cortical computations

The cerebral cortex can perform powerful computations, including those involved in higher cognitive functions. Cortical processing for such computations is executed by local circuits and is further enriched by long-range connectivity. This connectivity is activated under specific conditions and modulates local processing, providing flexibility in the computational performance of the cortex. For instance, long-range connectivity in the primary visual cortex exerts facilitatory impacts when the cortex is silent but suppressive impacts when the cortex is strongly sensory-stimulated. These dual impacts can be captured by a divisive gain control model. Recent methodological advances such as optogenetics, anatomical tracing, and two-photon microscopy have enabled neuroscientists to probe the circuit and synaptic bases of long-range connectivity in detail. Here, I review a series of evidence indicating essential roles of long-range connectivity in visual and hierarchical processing involving numerous cortical areas. I also describe an overview of the challenges encountered in investigating underlying synaptic mechanisms and highlight recent technical approaches that may overcome these difficulties and provide new insights into synaptic mechanisms for cortical processing involving long-range connectivity.

Transformation of Feature Selectivity From Membrane Potential to Spikes in the Mouse Superior Colliculus

Neurons in the visual system display varying degrees of selectivity for stimulus features such as orientation and direction. Such feature selectivity is generated and processed by intricate circuit and synaptic mechanisms. A key factor in this process is the input-output transformation from membrane potential (V_m) to spikes in individual neurons. Here, we use in vivo whole-cell recording to study V_m-to-spike transformation of visual feature selectivity in the superficial neurons of the mouse superior colliculus (SC). As expected from the spike threshold effect, direction and orientation selectivity increase from V_m to spike responses. The degree of this increase is highly variable, and interestingly, it is correlated with the receptive field size of the recorded neurons. We find that the relationships between V_m and spike rate and between V_m dynamics and spike initiation are also correlated with receptive field size, which likely contribute to the observed input-output transformation of feature selectivity. Together, our findings provide useful information for understanding information processing and visual transformation in the mouse SC.

Relationship between the Dynamics of Orientation Tuning and Spatiotemporal Receptive Field Structures of Cat LGN Neurons

Simple cells in the cat primary visual cortex usually have elongated receptive fields (RFs), and their orientation selectivity can be largely predicted by their RFs. As to the relay cells in cats' lateral geniculate nucleus (LGN), they also have weak but significant orientation bias (OB). It is thus of interest to investigate the fine spatiotemporal receptive field (STRF) properties in LGN, compare them with the dynamics of orientation tuning, and examine the dynamic relationship between STRF and orientation sensitivity in LGN. We mapped the STRFs of the LGN neurons in cats with white noise and characterized the dynamics of the orientation tuning by flashing gratings. We found that most of the LGN neurons showed elongated RFs and that the elongation axes were consistent with the preferred orientations. STRFs and the dynamics of orientation tuning were closely correlated temporally: the elongation of RFs and OB emerged, peaked and decayed at the same pace, with unchanged elongation axis of RF and preferred orientation but consistently changing aspect ratio of RF and OB strength across time. Importantly, the above consistency between RF and orientation tuning was not influenced by the ablation of the primary visual cortex. Furthermore, biased orientation tuning emerged 20-30 ms earlier than those in the primary visual cortex. These data demonstrated that similar to the primary visual cortex, the orientation sensitivity was closely reflected by the RF properties in LGN. However, the elongated RF and OB in LGN did not originate from the primary visual cortex feedback.

Mechanisms of Orientation Selectivity in the Primary Visual Cortex

The mechanisms underlying the emergence of orientation selectivity in the visual cortex have been, and continue to be, the subjects of intense scrutiny. Orientation selectivity reflects a dramatic change in the representation of the visual world: Whereas afferent thalamic neurons are generally orientation insensitive, neurons in the primary visual cortex (V1) are extremely sensitive to stimulus orientation. This profound change in the receptive field structure along the visual pathway has positioned V1 as a model system for studying the circuitry that underlies neural computations across the neocortex. The neocortex is characterized anatomically by the relative uniformity of its circuitry despite its role in processing distinct signals from region to region. A combination of physiological, anatomical, and theoretical studies has shed some light on the circuitry components necessary for generating orientation selectivity in V1. This targeted effort has led to critical insights, as well as controversies, concerning how neural circuits in the neocortex perform computations.

The divisive normalization model of V1 neurons: a comprehensive comparison of physiological data and model predictions

The physiological responses of simple and complex cells in the primary visual cortex (V1) have been studied extensively and modeled at different levels. At the functional level, the divisive normalization model (DNM; Heeger DJ. Vis Neurosci 9: 181-197, 1992) has accounted for a wide range of single-cell recordings in terms of a combination of linear filtering, nonlinear rectification, and divisive normalization. We propose standardizing the formulation of the DNM and implementing it in software that takes static grayscale images as inputs and produces firing rate responses as outputs. We also review a comprehensive suite of 30 empirical phenomena and report a series of simulation experiments that qualitatively replicate dozens of key experiments with a standard parameter set consistent with physiological measurements. This systematic approach identifies novel falsifiable predictions of the DNM. We show how the model simultaneously satisfies the conflicting desiderata of flexibility and falsifiability. Our key idea is that, while adjustable parameters are needed to accommodate the diversity across neurons, they must be fixed for a given individual neuron. This requirement introduces falsifiable constraints when this single neuron is probed with multiple stimuli. We also present mathematical analyses and simulation experiments that explicate some of these constraints.

Topographic Independent Component Analysis reveals random scrambling of orientation in visual space

Neurons at primary visual cortex (V1) in humans and other species are edge filters organized in orientation maps. In these maps, neurons with similar orientation preference are clustered together in iso-orientation domains. These maps have two fundamental properties: (1) retinotopy, i.e. correspondence between displacements at the image space and displacements at the cortical surface, and (2) a trade-off between good coverage of the visual field with all orientations and continuity of iso-orientation domains in the cortical space. There is an active debate on the origin of these locally continuous maps. While most of the existing descriptions take purely geometric/mechanistic approaches which disregard the network function, a clear exception to this trend in the literature is the original approach of Hyvärinen and Hoyer based on infomax and Topographic Independent Component Analysis (TICA). Although TICA successfully addresses a number of other properties of V1 simple and complex cells, in this work we question the validity of the orientation maps obtained from TICA. We argue that the maps predicted by TICA can be analyzed in the retinal space, and when doing so, it is apparent that they lack the required continuity and retinotopy. Here we show that in the orientation maps reported in the TICA literature it is easy to find examples of violation of the continuity between similarly tuned mechanisms in the retinal space, which suggest a random scrambling incompatible with the maps in primates. The new experiments in the retinal space presented here confirm this guess: TICA basis vectors actually follow a random salt-and-pepper organization back in the image space. Therefore, the interesting clusters found in the TICA topology cannot be interpreted as the actual cortical orientation maps found in cats, primates or humans. In conclusion, Topographic ICA does not reproduce cortical orientation maps.

Comparison of mechanisms for contrast-invariance of orientation selectivity in simple cells

The simple cells of the visual cortex respond over a narrow range of stimulus orientations, and this tuning is invariant to the contrast at which the stimulus is presented. The inputs to a single cell derive from a population of thalamic cells that provide a bell-shaped tuning width and offset that increases with stimulus contrast. Synaptic depression, noise and inhibition have been proposed as feedforward mechanisms to explain why these increases do not appear in simple cells. The extent to which these three mechanisms contribute to contrast-invariant orientation tuning is unknown. Consequently, the aim was to test the hypothesis that these mechanisms do not contribute equally. Unlike previous studies, all mechanisms were examined using the same network model based on Banitt et al. (2007). The results showed that thalamocortical synaptic noise was essential and sufficient to widen tuning widths at low contrasts to that of higher contrasts but could not counteract the offset at higher contrasts. Thalamocortical synaptic depression could only be used to counteract a small fraction of the offset otherwise the relationship between contrast and response rate was disrupted. Only broadly tuned simple and complex cell inhibition could counteract the remaining offset for all stimulus contrasts but complex cell inhibition reduced the gain of the response. These results suggest unequal contributions of these feedforward mechanisms with thalamic synaptic noise widening tuning widths for low contrasts, synaptic depression counteracting a small component of the offset and synaptic inhibition completely removing the remaining offset to produce contrast-invariant orientation tuning.

Orientation Tuning Depends on Spatial Frequency in Mouse Visual Cortex

The response properties of neurons to sensory stimuli have been used to identify their receptive fields and to functionally map sensory systems. In primary visual cortex, most neurons are selective to a particular orientation and spatial frequency of the visual stimulus. Using two-photon calcium imaging of neuronal populations from the primary visual cortex of mice, we have characterized the response properties of neurons to various orientations and spatial frequencies. Surprisingly, we found that the orientation selectivity of neurons actually depends on the spatial frequency of the stimulus. This dependence can be easily explained if one assumed spatially asymmetric Gabor-type receptive fields. We propose that receptive fields of neurons in layer 2/3 of visual cortex are indeed spatially asymmetric, and that this asymmetry could be used effectively by the visual system to encode natural scenes.

Topology of ON and OFF inputs in visual cortex enables an invariant columnar architecture

Circuits in visual cortex integrate the information derived from separate ON and OFF pathways to construct orderly columnar representations of orientation and visual space^1–7. How this transformation is achieved to meet the specific topographic constraints of each representation remains unclear. Here we report several novel features of ON/OFF convergence visualized by mapping the receptive fields of layer 2/3 neurons in tree shrew visual cortex using two-photon imaging of GCaMP6 calcium signals. The spatially separate ON and OFF subfields of simple cells in layer 2/3 were found to exhibit topologically distinct relationships with the maps of visual space and orientation preference. The centers of OFF subfields for neurons in a given region of cortex were confined to a compact region of visual space and displayed a smooth visuotopic progression. In contrast, the centers of the ON subfields were distributed over a wider region of visual space, displayed significant visuotopic scatter, and an orientation-specific displacement consistent with orientation preference map structure. As a result, cortical columns exhibit an invariant aggregate receptive field structure: an OFF-dominated central region flanked by ON-dominated subfields. This distinct arrangement of ON- and OFF- inputs enables continuity in the mapping of both orientation and visual space and the generation of a columnar map of absolute spatial phase.

Effect of Contrast on Visual Spatial Summation in Different Cell Categories in Cat Primary Visual Cortex

Multiple cell classes have been found in the primary visual cortex, but the relationship between cell types and spatial summation has seldom been studied. Parvalbumin-expressing inhibitory interneurons can be distinguished from pyramidal neurons based on their briefer action potential durations. In this study, we classified V1 cells into fast-spiking units (FSUs) and regular-spiking units (RSUs) and then examined spatial summation at high and low contrast. Our results revealed that the excitatory classical receptive field and the suppressive non-classical receptive field expanded at low contrast for both FSUs and RSUs, but the expansion was more marked for the RSUs than for the FSUs. For most V1 neurons, surround suppression varied as the contrast changed from high to low. However, FSUs exhibited no significant difference in the strength of suppression between high and low contrast, although the overall suppression decreased significantly at low contrast for the RSUs. Our results suggest that the modulation of spatial summation by stimulus contrast differs across populations of neurons in the cat primary visual cortex.

Synaptic Basis for Differential Orientation Selectivity between Complex and Simple Cells in Mouse Visual Cortex

In the primary visual cortex (V1), orientation-selective neurons can be categorized into simple and complex cells primarily based on their receptive field (RF) structures. In mouse V1, although previous studies have examined the excitatory/inhibitory interplay underlying orientation selectivity (OS) of simple cells, the synaptic bases for that of complex cells have remained obscure. Here, by combining in vivo loose-patch and whole-cell recordings, we found that complex cells, identified by their overlapping on/off subfields, had significantly weaker OS than simple cells at both spiking and subthreshold membrane potential response levels. Voltage-clamp recordings further revealed that although excitatory inputs to complex and simple cells exhibited a similar degree of OS, inhibition in complex cells was more narrowly tuned than excitation, whereas in simple cells inhibition was more broadly tuned than excitation. The differential inhibitory tuning can primarily account for the difference in OS between complex and simple cells. Interestingly, the differential synaptic tuning correlated well with the spatial organization of synaptic input: the inhibitory visual RF in complex cells was more elongated in shape than its excitatory counterpart and also was more elongated than that in simple cells. Together, our results demonstrate that OS of complex and simple cells is differentially shaped by cortical inhibition based on its orientation tuning profile relative to excitation, which is contributed at least partially by the spatial organization of RFs of presynaptic inhibitory neurons.

SIGNIFICANCE STATEMENT

Simple and complex cells, two classes of principal neurons in the primary visual cortex (V1), are generally thought to be equally selective for orientation. In mouse V1, we report that complex cells, identified by their overlapping on/off subfields, has significantly weaker orientation selectivity (OS) than simple cells. This can be primarily attributed to the differential tuning selectivity of inhibitory synaptic input: inhibition in complex cells is more narrowly tuned than excitation, whereas in simple cells inhibition is more broadly tuned than excitation. In addition, there is a good correlation between inhibitory tuning selectivity and the spatial organization of inhibitory inputs. These complex and simple cells with differential degree of OS may provide functionally distinct signals to different downstream targets.

Orientation selectivity in cat primary visual cortex: local and global measurement

In this study, we investigated orientation selectivity in cat primary visual cortex (V1) and its relationship with various parameters. We found a strong correlation between circular variance (CV) and orthogonal-topreferred response ratio (O/P ratio), and a moderate correlation between tuning width and O/P ratio. Moreover, the suppression far from the peak that accounted for the lower CV in cat V1 cells also contributed to the narrowing of the tuning width of cells. We also studied the dependence of orientation selectivity on the modulation ratio for each cell, which is consistent with robust entrainment of the neuronal response to the phase of the drifting grating stimulus. In conclusion, the CV (global measure) and tuning width (local measure) are signifi cantly correlated with the modulation ratio.

Neurons in cat V1 show significant clustering by degree of tuning

Neighboring neurons in cat primary visual cortex (V1) have similar preferred orientation, direction, and spatial frequency. How diverse is their degree of tuning for these properties? To address this, we used single-tetrode recordings to simultaneously isolate multiple cells at single recording sites and record their responses to flashed and drifting gratings of multiple orientations, spatial frequencies, and, for drifting gratings, directions. Orientation tuning width, spatial frequency tuning width, and direction selectivity index (DSI) all showed significant clustering: pairs of neurons recorded at a single site were significantly more similar in each of these properties than pairs of neurons from different recording sites. The strength of the clustering was generally modest. The percent decrease in the median difference between pairs from the same site, relative to pairs from different sites, was as follows: for different measures of orientation tuning width, 29-35% (drifting gratings) or 15-25% (flashed gratings); for DSI, 24%; and for spatial frequency tuning width measured in octaves, 8% (drifting gratings). The clusterings of all of these measures were much weaker than for preferred orientation (68% decrease) but comparable to that seen for preferred spatial frequency in response to drifting gratings (26%). For the above properties, little difference in clustering was seen between simple and complex cells. In studies of spatial frequency tuning to flashed gratings, strong clustering was seen among simple-cell pairs for tuning width (70% decrease) and preferred frequency (71% decrease), whereas no clustering was seen for simple-complex or complex-complex cell pairs.

The effects of short-term synaptic depression at thalamocortical synapses on orientation tuning in cat V1

We examine the effects of short-term synaptic depression on the orientation tuning of the LGN input to simple cells in cat primary visual cortex (V1). The total LGN input has an untuned component as well as a tuned component, both of which grow with stimulus contrast. The untuned component is not visible in the firing rate responses of the simple cells. The suppression of the contribution of the untuned input component to firing rate responses is key to establishing orientation selectivity and its invariance with stimulus contrast. It has been argued that synaptic depression of LGN inputs could contribute to the selective suppression of the untuned component and thus contribute to the tuning observed in simple cells. We examine this using a model fit to the depression observed at thalamocortical synapses in-vivo, and compare this to an earlier model fit based on in-vitro observations. We examine the tuning of both the conductance and the firing rate induced in simple cells by the net LGN input. We find that depression causes minimal suppression of the untuned component. The primary effect of depression is to cause the contrast response curve to saturate at lower contrasts without differentially affecting the tuned vs. untuned components. This effect is slightly weaker for in-vivo vs. in-vitro parameters. Thus, synaptic depression of LGN inputs does not appreciably contribute to the orientation tuning of V1 simple cells.

Linear transformation of thalamocortical input by intracortical excitation

Neurons in thalamorecipient layers of sensory cortices integrate thalamocortical and intracortical inputs. Although their functional properties can be inherited from the convergence of thalamic inputs, the roles of intracortical circuits in thalamocortical transformation of sensory information remain unclear. Here, by reversibly silencing intracortical excitatory circuits with optogenetic activation of parvalbumin-positive inhibitory neurons in mouse primary visual cortex, we compared visually-evoked thalamocortical input with total excitation in the same layer 4 pyramidal neurons. We found that intracortical excitatory circuits preserve the orientation and direction tuning of thalamocortical excitation, with a linear amplification of thalamocortical signals by about threefold. The spatial receptive field of thalamocortical input is slightly elongated, and is expanded by intracortical excitation in an approximately proportional manner. Thus, intracortical excitatory circuits faithfully reinforce the representation of thalamocortical information, and may influence the size of the receptive field by recruiting additional inputs.

Tuned thalamic excitation is amplified by visual cortical circuits

Cortical neurons in thalamic recipient layers receive excitation from the thalamus and the cortex. The relative contribution of these two sources of excitation to sensory tuning is poorly understood. We optogenetically silenced the visual cortex of mice to isolate thalamic excitation onto layer 4 neurons during visual stimulation. Thalamic excitation contributed to a third of the total excitation and was organized in spatially offset, yet overlapping, ON and OFF receptive fields. This receptive field structure predicted the orientation tuning of thalamic excitation. Finally, both thalamic and total excitation were similarly tuned to orientation and direction and had the same temporal phase relationship to the visual stimulus. Our results indicate that tuning of thalamic excitation is unlikely to be imparted by direction- or orientation-selective thalamic neurons and that a principal role of cortical circuits is to amplify tuned thalamic excitation.

On the relation between receptive field structure and stimulus selectivity in the tree shrew primary visual cortex

There are notable differences in functional properties of primary visual cortex (V1) neurons among mammalian species, particularly those concerning the occurrence of simple and complex cells and the generation of orientation selectivity. Here, we present quantitative data on receptive field (RF) structure, response modulation, and orientation tuning for single neurons in V1 of the tree shrew, a close relative of primates. We find that spatial RF subfield segregation, a criterion for identifying simple cells, was exceedingly small in the tree shrew V1. In contrast, many neurons exhibited elevated F1/F0 modulation that is often used as a simple cell marker. This apparent discrepancy can be explained by the robust stimulus polarity preference in tree shrew V1, which inflates F1/F0 ratio values. RF structure mapped with sparse-noise-which is spatially restricted and emphasizes thalamo-cortical feed-forward inputs-appeared unrelated to orientation selectivity. However, RF structure mapped using the Hartley subspace stimulus-which covers a large area of the visual field and recruits considerable intracortical processing-did predict orientation preference. Our findings reveal a number of striking similarities in V1 functional organization between tree shrews and primates, emphasizing the important role of intracortical recurrent processing in shaping V1 response properties in these species.

Functional connectivity and tuning curves in populations of simultaneously recorded neurons

How interactions between neurons relate to tuned neural responses is a longstanding question in systems neuroscience. Here we use statistical modeling and simultaneous multi-electrode recordings to explore the relationship between these interactions and tuning curves in six different brain areas. We find that, in most cases, functional interactions between neurons provide an explanation of spiking that complements and, in some cases, surpasses the influence of canonical tuning curves. Modeling functional interactions improves both encoding and decoding accuracy by accounting for noise correlations and features of the external world that tuning curves fail to capture. In cortex, modeling coupling alone allows spikes to be predicted more accurately than tuning curve models based on external variables. These results suggest that statistical models of functional interactions between even relatively small numbers of neurons may provide a useful framework for examining neural coding.

The number of simultaneous neurons that electrophysiologists can record is growing rapidly, and a central goal of computational neuroscience is to develop statistical methods that can make sense of this growing data. Here we present a unified statistical analysis of 10 different datasets recorded from several different species and brain areas. We show how functional interactions between neurons may be used to predict spiking in each of these different areas, and find that, in many cases, modeling interactions between a small number of neurons yields better spike predictions than modeling each neuron's relationship to the outside world using tuning curves. Although these statistical results cannot be linked to specific network architectures, since the measured interactions between neurons are purely functional rather than anatomical, they suggest that modeling interactions between neurons will be a useful approach to understanding neural coding as electrophysiologists record from increasing numbers of neurons.

Mechanisms of neuronal computation in mammalian visual cortex

Orientation selectivity in the primary visual cortex (V1) is a receptive field property that is at once simple enough to make it amenable to experimental and theoretical approaches and yet complex enough to represent a significant transformation in the representation of the visual image. As a result, V1 has become an area of choice for studying cortical computation and its underlying mechanisms. Here we consider the receptive field properties of the simple cells in cat V1--the cells that receive direct input from thalamic relay cells--and explore how these properties, many of which are highly nonlinear, arise. We have found that many receptive field properties of V1 simple cells fall directly out of Hubel and Wiesel's feedforward model when the model incorporates realistic neuronal and synaptic mechanisms, including threshold, synaptic depression, response variability, and the membrane time constant.

Effects of contrast and contrast adaptation on static receptive field features in macaque area V1

The spatiotemporal features of the “static” receptive field (RF), as revealed with flashing bars or spots, determine other RF properties. We examined how some of these static RF features vary with contrast and contrast adaptation in area V1 of the anesthetized macaque monkey. RFs were mapped with light and dark flashing bars presented at three different contrasts, with the low and medium contrasts eliciting approximately 1/3 and 2/3 of the high-contrast response amplitude. The main results are as follows: 1) RF widths decreased when contrast decreased; however, the amount of decrease was less than that expected from an iceberg model and closer to the expectation of a contrast invariance of the RF width. 2) Area tuning experiments with drifting gratings showed an opposite effect of contrast: an increase in preferred stimulus diameter when contrast decreased. This implies that the effect of contrast on preferred stimulus size is not predictable from the static RF. 3) Contrast adaptation attenuated the effect of contrast on RF amplitude but did not significantly modify RF width. 4) RF subregion overlap was only marginally affected by changes in contrast and contrast adaptation; the classification of cells as simple and complex, when established from subregion overlap, appears to be robust with respect to changes in contrast and adaptation state. Previous studies have shown that the spatiotemporal features of the RF depend largely on the stimuli used to map the RF. This study shows that contrast is one elemental feature that contributes to the dynamics of the RF.

Local circuit inhibition in the cerebral cortex as the source of gain control and untuned suppression

Theoretical considerations have led to the concept that the cerebral cortex is operating in a balanced state in which synaptic excitation is approximately balanced by synaptic inhibition from the local cortical circuit. This paper is about the functional consequences of the balanced state in sensory cortex. One consequence is gain control: there is experimental evidence and theoretical support for the idea that local circuit inhibition acts as a local automatic gain control throughout the cortex. Second, inhibition increases cortical feature selectivity: many studies of different sensory cortical areas have reported that suppressive mechanisms contribute to feature selectivity. Synaptic inhibition from the local microcircuit should be untuned (or broadly tuned) for stimulus features because of the microarchitecture of the cortical microcircuit. Untuned inhibition probably is the source of Untuned Suppression that enhances feature selectivity. We studied inhibition's function in our experiments, guided by a neuronal network model, on orientation selectivity in the primary visual cortex, V1, of the Macaque monkey. Our results revealed that Untuned Suppression, generated by local circuit inhibition, is crucial for the generation of highly orientation-selective cells in V1 cortex.

Development of orientation tuning in simple cells of primary visual cortex

Orientation selectivity and its development are basic features of visual cortex. The original model of orientation selectivity proposes that elongated simple cell receptive fields are constructed from convergent input of an array of lateral geniculate nucleus neurons. However, orientation selectivity of simple cells in the visual cortex is generally greater than the linear contributions based on projections from spatial receptive field profiles. This implies that additional selectivity may arise from intracortical mechanisms. The hierarchical processing idea implies mainly linear connections, whereas cortical contributions are generally considered to be nonlinear. We have explored development of orientation selectivity in visual cortex with a focus on linear and nonlinear factors in a population of anesthetized 4-wk postnatal kittens and adult cats. Linear contributions are estimated from receptive field maps by which orientation tuning curves are generated and bandwidth is quantified. Nonlinear components are estimated as the magnitude of the power function relationship between responses measured from drifting sinusoidal gratings and those predicted from the spatial receptive field. Measured bandwidths for kittens are slightly larger than those in adults, whereas predicted bandwidths are substantially broader. These results suggest that relatively strong nonlinearities in early postnatal stages are substantially involved in the development of orientation tuning in visual cortex.

Broad inhibition sharpens orientation selectivity by expanding input dynamic range in mouse simple cells

Orientation selectivity (OS) is an emergent property in the primary visual cortex (V1). How OS arises from synaptic circuits remains unsolved. Here, in vivo whole-cell recordings in the mouse V1 revealed that simple cells received broadly tuned excitation and even more broadly tuned inhibition. Excitation and inhibition shared a similar orientation preference and temporally overlapped substantially. Neuron modeling and dynamic-clamp recording further revealed that excitatory inputs alone would result in membrane potential responses with significantly attenuated selectivity, due to a saturating input-output function of the membrane filtering. Inhibition ameliorated the attenuation of excitatory selectivity by expanding the input dynamic range and caused additional sharpening of output responses beyond unselectively suppressing responses at all orientations. This "blur-sharpening" effect allows selectivity conveyed by excitatory inputs to be better expressed, which may be a general mechanism underlying the generation of feature-selective responses in the face of strong excitatory inputs that are weakly biased.

Role of feedforward geniculate inputs in the generation of orientation selectivity in the cat's primary visual cortex

Neurones of the mammalian primary visual cortex have the remarkable property of being selective for the orientation of visual contours. It has been controversial whether the selectivity arises from intracortical mechanisms, from the pattern of afferent connectivity from lateral geniculate nucleus (LGN) to cortical cells or from the sharpening of a bias that is already present in the responses of many geniculate cells. To investigate this, we employed a variation of an electrical stimulation protocol in the LGN that has been claimed to suppress intra cortical inputs and isolate the raw geniculocortical input to a striate cortical cell. Such stimulation led to a sharpening of the orientation sensitivity of geniculate cells themselves and some broadening of cortical orientation selectivity. These findings are consistent with the idea that non-specific inhibition of the signals from LGN cells which exhibit an orientation bias can generate the sharp orientation selectivity of primary visual cortical cells. This obviates the need for an excitatory convergence from geniculate cells whose receptive fields are arranged along a row in visual space as in the classical model and provides a framework for orientation sensitivity originating in the retina and getting sharpened through inhibition at higher levels of the visual pathway.

Mechanisms of direction selectivity in cat primary visual cortex as revealed by visual adaptation

In contrast to neurons of the lateral geniculate nucleus (LGN), neurons in the primary visual cortex (V1) are selective for the direction of visual motion. Cortical direction selectivity could emerge from the spatiotemporal configuration of inputs from thalamic cells, from intracortical inhibitory interactions, or from a combination of thalamic and intracortical interactions. To distinguish between these possibilities, we studied the effect of adaptation (prolonged visual stimulation) on the direction selectivity of intracellularly recorded cortical neurons. It is known that adaptation selectively reduces the responses of cortical neurons, while largely sparing the afferent LGN input. Adaptation can therefore be used as a tool to dissect the relative contribution of afferent and intracortical interactions to the generation of direction selectivity. In both simple and complex cells, adaptation caused a hyperpolarization of the resting membrane potential (-2.5 mV, simple cells, -0.95 mV complex cells). In simple cells, adaptation in either direction only slightly reduced the visually evoked depolarization; this reduction was similar for preferred and null directions. In complex cells, adaptation strongly reduced visual responses in a direction-dependent manner: the reduction was largest when the stimulus direction matched that of the adapting motion. As a result, adaptation caused changes in the direction selectivity of complex cells: direction selectivity was reduced after preferred direction adaptation and increased after null direction adaptation. Because adaptation in the null direction enhanced direction selectivity rather than reduced it, it seems unlikely that inhibition from the null direction is the primary mechanism for creating direction selectivity.

Correlation between spatial frequency and orientation selectivity in V1 cortex: implications of a network model

We addressed how spatial frequency and orientation selectivity coexist and co-vary in Macaque primary visual cortex (V1) by simulating cortical layer 4Cα of V1 with a large-scale network model and then comparing the model's behavior with a population of cells we recorded in layer 4Cα. We compared the distributions of orientation and spatial frequency selectivity, as well as the correlation between the two, in the model with what we observed in the 4Cα population. We found that (1) in the model, both spatial frequency and orientation selectivity of neuronal firing are greater and more diverse than the LGN inputs to model neurons; (2) orientation and spatial frequency selectivity co-vary in the model in a way very similar to what we observed in layer 4Cα neurons; (3) in the model, orientation and spatial frequency selectivity co-vary because of intra-cortical inhibition. The results suggest that cortical inhibition provides a common mechanism for selectivity in multiple dimensions.

Spatial and temporal features of synaptic to discharge receptive field transformation in cat area 17

The aim of the present study was to characterize the spatial and temporal features of synaptic and discharge receptive fields (RFs), and to quantify their relationships, in cat area 17. For this purpose, neurons were recorded intracellularly while high-frequency flashing bars were used to generate RFs maps for synaptic and spiking responses. Comparison of the maps shows that some features of the discharge RFs depended strongly on those of the synaptic RFs, whereas others were less dependent. Spiking RF duration depended poorly and spiking RF amplitude depended moderately on those of the underlying synaptic RFs. At the other extreme, the optimal spatial frequency and phase of the discharge RFs in simple cells were almost entirely inherited from those of the synaptic RFs. Subfield width, in both simple and complex cells, was less for spiking responses compared with synaptic responses, but synaptic to discharge width ratio was relatively variable from cell to cell. When considering the whole RF of simple cells, additional variability in width ratio resulted from the presence of additional synaptic subfields that remained subthreshold. Due to these additional, subthreshold subfields, spatial frequency tuning predicted from synaptic RFs appears sharper than that predicted from spiking RFs. Excitatory subfield overlap in spiking RFs was well predicted by subfield overlap at the synaptic level. When examined in different regions of the RF, latencies appeared to be quite variable, but this variability showed negligible dependence on distance from the RF center. Nevertheless, spiking response latency faithfully reflected synaptic response latency.

Models and Measurements of Functional Maps in V1

The organization of primary visual cortex has been heavily studied for nearly 50 years, and in the last 20 years functional imaging has provided high-resolution maps of its tangential organization. Recently, however, the usefulness of maps like those of orientation and spatial frequency (SF) preference has been called into question because they do not, by themselves, predict how moving images are represented in V1. In this review, we discuss a model for cortical responses (the spatiotemporal filtering model) that specifies the types of cortical maps needed to predict distributed activity within V1. We then review the structure and interrelationships of several of these maps, including those of orientation, SF, and temporal frequency preference. Finally, we discuss tests of the model and the sufficiency of the requisite maps in predicting distributed cortical responses. Although the spatiotemporal filtering model does not account for all responses within V1, it does, with reasonable accuracy, predict population responses to a variety of complex stimuli.

The extraction of features and disparities from images by a model based on the neurological organisation of the visual system

A computational simulation of the early stages of mammalian visual processing, from the retina to the primary visual cortex, is described. The simulation uses elements that are organised according to the anatomical connections of the biological visual system. It explores how observed responses of simple cells of the primary visual cortex can be generated by a small number of stages of the types of processing that are observed in the nervous system. Edge features are extracted from single images and disparities between stereoscopic image pairs are detected with good reliability. An important parameter affecting processing was found to be the strength of the surround inhibition between the elements that represent neurones of the primary visual cortex.

Inhibition, spike threshold, and stimulus selectivity in primary visual cortex

Ever since Hubel and Wiesel described orientation selectivity in the visual cortex, the question of how precise selectivity emerges has been marked by considerable debate. There are essentially two views of how selectivity arises. Feed-forward models rely entirely on the organization of thalamocortical inputs. Feedback models rely on lateral inhibition to refine selectivity relative to a weak bias provided by thalamocortical inputs. The debate is driven by two divergent lines of evidence. On the one hand, many response properties appear to require lateral inhibition, including precise orientation and direction selectivity and crossorientation suppression. On the other hand, intracellular recordings have failed to find consistent evidence for lateral inhibition. Here we demonstrate a resolution to this paradox. Feed-forward models incorporating the intrinsic nonlinear properties of cortical neurons and feed-forward circuits (i.e., spike threshold, contrast saturation, and spike-rate rectification) can account for properties that have previously appeared to require lateral inhibition.

Visual stimuli modulate precise synchronous firing within the thalamus

The work of Mircea Steriade demonstrated that the neocortex could synchronize large regions of the thalamus within 10-100 milliseconds (for review see Steriade and Timofeev, 2003, Steriade, 2005). Unlike the synchrony generated by the cortex, the retinal afferents synchronize a restricted group of neighboring thalamic neurons with <1-millisecond precision (Alonso et al., 1996, Yeh et al., 2003). Here, we use a large sample (n= 372) of simultaneous recordings from neighboring neurons in the Lateral Geniculate Nucleus (LGN) to illustrate the high specificity of the synchrony generated by retinal afferents and its dependency on sensory stimulation. First, we demonstrate that cells sharing a retinal afferent show a balanced receptive field diversity: while slight receptive field mismatches are common, the largest mismatches in a specific property (e.g. receptive field size) are restricted to cells that are precisely matched in other properties (e.g. receptive field overlap). Second, we show that these receptive field mismatches are functionally important and can lead to a 5-fold variation in the percentage of synchronous spikes driven by the shared retinal afferent under different stimulus conditions. Based on these and other findings, we speculate that the precise synchronous firing of cells sharing a retinal afferent could serve to amplify local stimuli that may be too brief and small to generate a large number of thalamic spikes.

Stimulus feature selectivity in excitatory and inhibitory neurons in primary visual cortex

Although several lines of evidence suggest that stimulus selectivity in somatosensory and visual cortices is critically dependent on unselective inhibition, particularly in the thalamorecipient layer 4, no comprehensive comparison of the responses of excitatory and inhibitory cells has been conducted. Here, we recorded intracellularly from a large population of regular spiking (RS; presumed excitatory) and fast spiking (FS; presumed inhibitory) cells in layers 2-6 of primary visual cortex. In layer 4, where selectivity for orientation and spatial frequency first emerges, we found no untuned FS cells. Instead, the tuning of the spike output of layer 4 FS cells was significantly but moderately broader than that of RS cells. However, the tuning of the underlying synaptic responses was not different, indicating that the difference in spike-output selectivity resulted from differences in the transformation of synaptic input into firing rate. Layer 4 FS cells exhibited significantly lower input resistance and faster time constants than layer 4 RS cells, leading to larger and faster membrane potential (V(m)) fluctuations. FS cell V(m) fluctuations were more broadly tuned than those of RS cells and matched spike-output tuning, suggesting that the broader spike tuning of these cells was driven by visually evoked synaptic noise. These differences were not observed outside of layer 4. Thus, cell type-specific differences in stimulus feature selectivity at the first level of cortical sensory processing may arise as a result of distinct biophysical properties that determine the dynamics of synaptic integration.

Neurophysiological and simulation studies of striate cortex receptive field maps: the role of intracortical interneuronal interactions

Acute experiments on 27 adult anesthetized and immobilized cats investigated 101 on and off receptive fields in 67 neurons in visual cortex field 17 by mapping using single local stimuli presented sequentially at different parts of the visual field, as well as in combination with additional stimulation of the center of the receptive field. Both classical and combined mapping identified receptive fields with single receptive zones (63.4% and 29.3% respectively), along with fields consisting of several (2-5) excitatory and/or inhibitory zones (36.6% and 70.7%). We provide the first report of receptive fields with horseshoe, cross, and T shapes. Simulations of horizontal interneuronal interactions in the visual cortex responsible for the multiplicity of excitatory and inhibitory zones of receptive fields were performed. A role for cooperative interactions of neurons in this effect was demonstrated. The possible functional role of receptive fields of different types in extracting the features of visual images is discussed.

The emergence of contrast-invariant orientation tuning in simple cells of cat visual cortex

Simple cells in primary visual cortex exhibit contrast-invariant orientation tuning, in seeming contradiction to feed-forward models that rely on lateral geniculate nucleus (LGN) input alone. Contrast invariance has therefore been thought to depend on the presence of intracortical lateral inhibition. In vivo intracellular recordings instead suggest that contrast invariance can be explained by three properties of the excitatory pathway. (1) Depolarizations evoked by orthogonal stimuli are determined by the amount of excitation a cell receives from the LGN, relative to the excitation it receives from other cortical cells. (2) Depolarizations evoked by preferred stimuli saturate at lower contrasts than the spike output of LGN relay cells. (3) Visual stimuli evoke contrast-dependent changes in trial-to-trial variability, which lead to contrast-dependent changes in the relationship between membrane potential and spike rate. Thus, high-contrast, orthogonally oriented stimuli that evoke significant depolarizations evoke few spikes. Together these mechanisms, without lateral inhibition, can account for contrast-invariant stimulus selectivity.

The generation of receptive-field structure in cat primary visual cortex

Cells in primary visual cortex show a remarkable variety of receptive-field structures. In spite of the extensive experimental and theoretical effort over the past 50 years, it has been difficult to establish how this diversity of functional-response properties emerges in the cortex. One of the reasons is that while functional studies in the early visual pathway have been usually carried out in vivo with extracellular recording techniques, investigations about the precise structure of the cortical network have mainly been conducted in vitro. Thus, the link between structure and function has rarely been explicitly established, remaining a well-known controversial issue. In this chapter, I review recent data that simultaneously combines anatomy with physiology at the intracellular level; trying to understand how the primary visual cortex transforms the information it receives from the thalamus to generate receptive-field structure, contrast-invariant orientation tuning and other functional-response properties.

Circuits that build visual cortical receptive fields

Neural sensitivity to basic elements of the visual scene changes dramatically as information is handed from the thalamus to the primary visual cortex in cats. Famously, thalamic neurons are insensitive to stimulus orientation whereas their cortical targets easily resolve small changes in stimulus angle. There are two main types of cells in the visual cortex, simple and complex, defined by the structure of their receptive fields. Simple cells are thought to lay the groundwork for orientation selectivity. This review focuses on approaches that combine anatomy with physiology at the intracellular level, to explore the circuits that build simple receptive fields and that help to maintain neural sensitivity to stimulus features even when luminance contrast changes.

Do we know what the early visual system does?

We can claim that we know what the visual system does once we can predict neural responses to arbitrary stimuli, including those seen in nature. In the early visual system, models based on one or more linear receptive fields hold promise to achieve this goal as long as the models include nonlinear mechanisms that control responsiveness, based on stimulus context and history, and take into account the nonlinearity of spike generation. These linear and nonlinear mechanisms might be the only essential determinants of the response, or alternatively, there may be additional fundamental determinants yet to be identified. Research is progressing with the goals of defining a single "standard model" for each stage of the visual pathway and testing the predictive power of these models on the responses to movies of natural scenes. These predictive models represent, at a given stage of the visual pathway, a compact description of visual computation. They would be an invaluable guide for understanding the underlying biophysical and anatomical mechanisms and relating neural responses to visual perception.

Local networks in visual cortex and their influence on neuronal responses and dynamics

Networks of neurons in the cerebral cortex generate complex outputs that are not simply predicted by their inputs. These emergent responses underlie the function of the cortex. Understanding how cortical networks carry out such transformations requires a description of the responses of individual neurons and of their networks at multiple levels of analysis. We focus on orientation selectivity in primary visual cortex as a model system to understand cortical network computations. Recent experiments in our laboratory and others provide significant insight into how cortical networks generate and maintain orientation selectivity. We first review evidence for the diversity of orientation tuning characteristics in visual cortex. We then describe experiments that combine optical imaging of orientation maps with intracellular and extracellular recordings from individual neurons at known locations in the orientation map. The data indicate that excitatory and inhibitory synaptic inputs are summed across the cortex in a manner that is consistent with simple rules of integration of local inputs. These rules arise from known anatomical projection patterns in visual cortex. We propose that the generation and plasticity of orientation tuning is strongly influenced by local cortical networks-the diversity of these properties arises in part from the diversity of neighbourhood features that derive from the orientation map.

Coding of color and form in the geniculostriate visual pathway (invited review)

We review how neurons in the principal pathway connecting the retina to the visual cortex represent information about the chromatic and spatial characteristics of the retinal image. Our examination focuses particularly on individual neurons: what are their visual properties, how might these properties arise, what do these properties tell us about visual signal transformations, and how might these properties be expressed in perception? Our discussion is inclined toward studies on old-world monkeys and where possible emphasizes quantitative work that has led to or illuminates models of visual signal processing.

Thalamocortical specificity and the synthesis of sensory cortical receptive fields

A persistent and fundamental question in sensory cortical physiology concerns the manner in which receptive fields of layer-4 neurons are synthesized from their thalamic inputs. According to a hierarchical model proposed more than 40 years ago, simple receptive fields in layer 4 of primary visual cortex originate from the convergence of highly specific thalamocortical inputs (e.g., geniculate inputs with on-center receptive fields overlap the on subregions of layer 4 simple cells). Here, we summarize studies in the visual cortex that provide support for this high specificity of thalamic input to visual cortical simple cells. In addition, we review studies of GABAergic interneurons in the somatosensory "barrel" cortex with receptive fields that are generated by a very different mechanism: the nonspecific convergence of thalamic inputs with different response properties. We hypothesize that these 2 modes of thalamocortical connectivity onto subpopulations of excitatory and inhibitory neurons constitute a general feature of sensory neocortex and account for much of the diversity seen in layer-4 receptive fields.

Invariant computations in local cortical networks with balanced excitation and inhibition

Cortical computations critically involve local neuronal circuits. The computations are often invariant across a cortical area yet are carried out by networks that can vary widely within an area according to its functional architecture. Here we demonstrate a mechanism by which orientation selectivity is computed invariantly in cat primary visual cortex across an orientation preference map that provides a wide diversity of local circuits. Visually evoked excitatory and inhibitory synaptic conductances are balanced exquisitely in cortical neurons and thus keep the spike response sharply tuned at all map locations. This functional balance derives from spatially isotropic local connectivity of both excitatory and inhibitory cells. Modeling results demonstrate that such covariation is a signature of recurrent rather than purely feed-forward processing and that the observed isotropic local circuit is sufficient to generate invariant spike tuning.

Bottom-up and top-down dynamics in visual cortex

A key emergent property of the primary visual cortex (V1) is the orientation selectivity of its neurons. Recent experiments demonstrate remarkable bottom-up and top-down plasticity in orientation networks of the adult cortex. The basis for such dynamics is the mechanism by which orientation tuning is created and maintained, by integration of thalamocortical and intracortical inputs. Intracellular measurements of excitatory and inhibitory synaptic conductances reveal that excitation and inhibition balance each other at all locations in the cortex. This balance is particularly critical at pinwheel centers of the orientation map, where neurons receive intracortical input from a wide diversity of local orientations. The orientation tuning of neurons in adult V1 changes systematically after short-term exposure to one stimulus orientation. Such reversible physiological shifts in tuning parallel the orientation tilt aftereffect observed psychophysically. Neurons at or near pinwheel centers show pronounced changes in orientation preference after adaptation with an oriented stimulus, while neurons in iso-orientation domains show minimal changes. Neurons in V1 of alert, behaving monkeys also exhibit short-term orientation plasticity after very brief adaptation with an oriented stimulus, on the time scale of visual fixation. Adaptation with stimuli that are orthogonal to a neuron's preferred orientation does not alter the preferred orientation but sharpens orientation tuning. Thus, successive fixation on dissimilar image patches, as happens during natural vision, combined with mechanisms of rapid cortical plasticity, actually improves orientation discrimination. Finally, natural vision involves judgements about where to look next, based on an internal model of the visual world. Experiments in behaving monkeys in which information about future stimulus locations can be acquired in one set of trials but not in another demonstrate that V1 neurons signal the acquisition of internal representations. Such Bayesian updating of responses based on statistical learning is fundamental for higher level vision, for deriving inferences about the structure of the visual world, and for the regulation of eye movements.

The contribution of spike threshold to the dichotomy of cortical simple and complex cells

The existence of two classes of cells, simple and complex, discovered by Hubel and Wiesel in 1962, is one of the fundamental features of cat primary visual cortex. A quantitative measure used to distinguish simple and complex cells is the ratio between modulated and unmodulated components of spike responses to drifting gratings, an index that forms a bimodal distribution. We have found that the modulation ratio, when derived from the subthreshold membrane potential instead of from spike rate, is unimodally distributed, but highly skewed. The distribution of the modulation ratio as derived from spike rate can, in turn, be predicted quantitatively by the nonlinear properties of spike threshold applied to the skewed distribution of the subthreshold modulation ratio. Threshold also increases the spatial segregation of ON and OFF regions of the receptive field, a defining attribute of simple cells. The distinction between simple and complex cells is therefore enhanced by threshold, much like the selectivity for stimulus features such as orientation and direction. In this case, however, a continuous distribution in the spatial organization of synaptic inputs is transformed into two distinct classes of cells.

Intracellular measurements of spatial integration and the MAX operation in complex cells of the cat primary visual cortex

We have examined the spatial integration properties of complex cells to determine whether some of their responses can be described by a maximum operation (MAX)-like computation, as suggested by Riesenhuber and Poggio's model of object recognition. Membrane potential was recorded from anesthetized cats while optimally oriented bars were presented, either alone or in pairs, in different parts of the cells' receptive field. In most cells, the membrane potential response to two bars presented simultaneously could not be predicted by the sum of the responses to individual bars. In many cells, however, the responses closely approximated a MAX-like model. That is, the response of the cell to two bars was similar to the larger of the two individual responses ("soft-MAX"). The degree of nonlinear summation varied from cell to cell and varied within single cells from one stimulus configuration to another but on average fit most closely to the MAX model. The firing response of the cells was also well predicted by the MAX-like model. The MAX-like behavior was independent of the distance between the bars (orthogonal to the preferred orientation), independent of the relative amplitude of the responses, and slightly less pronounced at low levels of contrast. This MAX-like behavior of a subset of complex cells may play an important role in invariant object recognition in clutter.

The contribution of vertical and horizontal connections to the receptive field center and surround in V1

Here we review the results of anatomical and physiological studies in tree shrew visual cortex which focus on the contribution of vertical and horizontal inputs to receptive field center and surround properties of layer 2/3 neurons. A fundamental feature of both sets of connections is the arrangement of axon arbors in a fashion that respects both the orientation preference and retinotopic displacement of the target site. As a result, layer 2/3 neurons receive convergent input from populations of layer 4 and other layer 2/3 neurons whose receptive fields are displaced along an axis in visual space that corresponds to their preferred orientation. Although, horizontal connections extend for greater distances across the cortical surface than vertical connections, the majority of these inputs link neurons with overlapping receptive fields, emphasizing that both feed-forward and recurrent circuits are likely to play a constructive role in generating properties (such as orientation selectivity) that define the receptive field center. Both within and beyond the dimensions of the receptive field center, the distribution of horizontal connections accords remarkably well with the magnitude and axial tuning of length summation effects. Taken together, these results suggest a continuum of functional properties that transcends the traditional designation of receptive field center and surround. By extension, we suggest that the perceptual effects of stimulus context may arise from stimulus interactions within the receptive field center as well as between center and surround.

Complex receptive fields in primary visual cortex

In the early 1960s, Hubel and Wiesel reported the first physiological description of cells in cat primary visual cortex. They distinguished two main cell types: simple cells and complex cells. Based on their distinct response properties, they suggested that the two cell types could represent two consecutive stages in receptive-field construction. Since the 1960s, new experimental and computational evidence provided serious alternatives to this hierarchical model. Parallel models put forward the idea that both simple and complex receptive fields could be built in parallel by direct geniculate inputs. Recurrent models suggested that simple cells and complex cells may not be different cell types after all. To this day, a consensus among hierarchical, parallel, and recurrent models has been difficult to attain; however, the circuitry used by all models is becoming increasingly similar. The authors review theoretical and experimental evidence for each line of models emphasizing their strengths and weaknesses.

The nature of V1 neural responses to 2D moving patterns depends on receptive-field structure in the marmoset monkey

A plaid pattern is formed when two sinusoidal gratings of different orientations are added together. Previous work has shown that V1 neurons selectively encode the direction and orientation of the component gratings in a moving plaid but not the direction of the plaid itself (Movshon et al. 1985). We recorded the responses of 49 direction-selective neurons to moving gratings and plaid patterns in area V1 of the anesthetized marmoset monkey (Callithrix jacchus). The responses of V1 neurons to rectangular patches of varying lengths and widths containing gratings of optimal spatial frequency were used to measure size and aspect ratio of the receptive-field subunits. We measured responses to plaid patterns moving in different directions and graded the magnitude of the response to the direction of motion of the plaid and the response to the direction of motion of the component gratings. We found significant correlations between receptive-field structure and the type and strength of its response to moving plaid patterns. The strength of pattern and component responses was significantly correlated with the interrelated properties of direction tuning width (Spearman's r = 0.82, P < 0.001), and receptive-field subunit aspect ratio (Spearman's r = -0.79, P < 0.001). Neurons with broad direction tuning and short, wide receptive-field subunits gave their greatest response when the plaid moved in their preferred direction. Conversely, neurons with narrow direction tuning and long, narrow receptive-field subunits gave their greatest responses when the plaid moved in a direction such that one of its components moved in the preferred direction.